NEMESYS: Enhanced Network Security for Seamless Service Provisioning in the Smart Mobile Ecosystem

As a consequence of the growing popularity of smart mobile devices, mobile malware is clearly on the rise, with attackers targeting valuable user information and exploiting vulnerabilities of the mobile ecosystems. With the emergence of large-scale mobile botnets, smartphones can also be used to launch attacks on mobile networks. The NEMESYS project will develop novel security technologies for seamless service provisioning in the smart mobile ecosystem, and improve mobile network security through better understanding of the threat landscape. NEMESYS will gather and analyze information about the nature of cyber-attacks targeting mobile users and the mobile network so that appropriate counter-measures can be taken. We will develop a data collection infrastructure that incorporates virtualized mobile honeypots and a honeyclient, to gather, detect and provide early warning of mobile attacks and better understand the modus operandi of cyber-criminals that target mobile devices. By correlating the extracted information with the known patterns of attacks from wireline networks, we will reveal and identify trends in the way that cyber-criminals launch attacks against mobile devices.Comment: Accepted for publication in Proceedings of the 28th International Symposium on Computer and Information Sciences (ISCIS'13); 9 pages; 1 figur

Comparison of Empirical Data from Two Honeynets and a Distributed Honeypot Network

In this paper we present empirical results and speculative analysis based on observations collected over a two month period from studies with two high interaction honeynets, deployed in a corporate and an SME (small to medium enterprise) environment, and a distributed honeypots deployment. All three networks contain a mixture of Windows and Linux hosts. We detail the architecture of the deployment and results of comparing the observations from the three environments. We analyze in detail the times between attacks on different hosts, operating systems, networks or geographical location. Even though results from honeynet deployments are reported often in the literature, this paper provides novel results analyzing traffic from three different types of networks and some initial exploratory models. This research aims to contribute to endeavours in the wider security research community to build methods, grounded on strong empirical work, for assessment of the robustness of computer-based systems in hostile environments

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Towards Identifying Human Actions, Intent, and Severity of APT Attacks Applying Deception Techniques -- An Experiment

Attacks by Advanced Persistent Threats (APTs) have been shown to be difficult to detect using traditional signature- and anomaly-based intrusion detection approaches. Deception techniques such as decoy objects, often called honey items, may be deployed for intrusion detection and attack analysis, providing an alternative to detect APT behaviours. This work explores the use of honey items to classify intrusion interactions, differentiating automated attacks from those which need some human reasoning and interaction towards APT detection. Multiple decoy items are deployed on honeypots in a virtual honey network, some as breadcrumbs to detect indications of a structured manual attack. Monitoring functionality was created around Elastic Stack with a Kibana dashboard created to display interactions with various honey items. APT type manual intrusions are simulated by an experienced pentesting practitioner carrying out simulated attacks. Interactions with honey items are evaluated in order to determine their suitability for discriminating between automated tools and direct human intervention. The results show that it is possible to differentiate automatic attacks from manual structured attacks; from the nature of the interactions with the honey items. The use of honey items found in the honeypot, such as in later parts of a structured attack, have been shown to be successful in classification of manual attacks, as well as towards providing an indication of severity of the attack

Securing Distributed Computer Systems Using an Advanced Sophisticated Hybrid Honeypot Technology

Computer system security is the fastest developing segment in information technology. The conventional approach to system security is mostly aimed at protecting the system, while current trends are focusing on more aggressive forms of protection against potential attackers and intruders. One of the forms of protection is also the application of advanced technology based on the principle of baits - honeypots. Honeypots are specialized devices aimed at slowing down or diverting the attention of attackers from the critical system resources to allow future examination of the methods and tools used by the attackers. Currently, most honeypots are being configured and managed statically. This paper deals with the design of a sophisticated hybrid honeypot and its properties having in mind enhancing computer system security. The architecture of a sophisticated hybrid honeypot is represented by a single device capable of adapting to a constantly changing environment by using active and passive scanning techniques, which mitigate the disadvantages of low-interaction and high-interaction honeypots. The low-interaction honeypot serves as a proxy for multiple IP addresses and filters out traffic beyond concern, while the high-interaction honeypot provides an optimum level of interaction. The proposed architecture employing the prototype of a hybrid honeypot featuring autonomous operation should represent a security mechanism minimizing the disadvantages of intrusion detection systems and can be used as a solution to increase the security of a distributed computer system rapidly, both autonomously and in real-time

Scalable Honeypot Monitoring and Analytics

Honeypot systems with a large number of instances pose new challenges in terms of monitoring and analytics. They produce a significant amount of data and require the analyst to monitor every new honeypot instance in the system. Specifically, current approaches require each honeypot instance to be monitored and analysed individually. Therefore, these cannot scale to support scenarios in which a large number of honeypots are used. Furthermore, amalgamating data from a large number of honeypots presents new opportunities to analyse trends. This thesis proposes a scalable monitoring and analytics system that is designed to address this challenge. It consists of three components: monitoring, analysis and visualisation. The system automatically monitors each new honeypot, reduces the amount of collected data and stores it centrally. All gathered data is analysed in order to identify patterns of attacker behaviour. Visualisation conveniently displays the analysed data to an analyst. A user study was performed to evaluate the system. It shows that the solution has met the requirements posed to a scalable monitoring and analytics system. In particular, the monitoring and analytics can be implemented using only open-source software and does not noticeably impact the performance of individual honeypots or the scalability of the overall honeypot system. The thesis also discusses several variations and extensions, including detection of new patterns, and the possibility of providing feedback when used in an educational setting, monitoring attacks by information-security students

A Threat to Cyber Resilience : A Malware Rebirthing Botnet

This paper presents a threat to cyber resilience in the form of a conceptual model of a malware rebirthing botnet which can be used in a variety of scenarios. It can be used to collect existing malware and rebirth it with new functionality and signatures that will avoid detection by AV software and hinder analysis. The botnet can then use the customized malware to target an organization with an orchestrated attack from the member machines in the botnet for a variety of malicious purposes, including information warfare applications. Alternatively, it can also be used to inject known malware signatures into otherwise non malicious code and traffic to overloading the sensors and processing systems employed by intrusion detection and prevention systems to create a denial of confidence of the sensors and detection systems. This could be used as a force multiplier in asymmetric warfare applications to create confusion and distraction whilst attacks are made on other defensive fronts